AI could boost labor productivity by 3.8%, says IMF
What's the story
The International Monetary Fund (IMF) has released a working paper revealing that artificial intelligence (AI) could boost aggregate labor productivity by as much as 3.8% in the long run. The study analyzed patent and employment data from developed economies, finding that the rapid growth of AI-related innovation has already led to measurable productivity gains. Between 2000 and 2017, AI patent activity is estimated to have boosted output per worker by between 0.8% and 1.2%.
Research
Surge in AI-related patents since 2000
The IMF study, titled "Artificial Intelligence and Aggregate Labor Productivity: Evidence from Patent Data," looked at the overall impact of AI technology on labor productivity using patent data from OECD member countries.
It found that the number of patents related to AI technology surged after 2000, more than tripling by 2017.
During this period, OECD countries accounted for about 89% of all AI-related patents issued worldwide.
Future potential
Production-function approach reveals potential long-term gains
The researchers used a production-function approach to see if the rising number of AI patent applications translated into higher output per worker.
Their estimates indicate that as technological development accelerates and spreads across industries, AI innovation could lead to much larger productivity gains in the future.
The potential increase of up to 3.8% is a long-term estimate and would depend on continued development and wider adoption of these technologies across different sectors of the economy.
Uneven impact
Disparities in productivity gains across countries and job types
The study also notes that the benefits of AI are unlikely to be evenly distributed across countries or employment categories.
Countries with a high share of workers in professional and managerial occupations saw larger productivity gains from AI technology.
This suggests that economic returns from AI may be higher when it complements skilled labor rather than simply automating existing tasks.
Key factors
Need for worker adaptation and labor-market flexibility
The paper emphasizes that the speed at which workers adapt to new systems and integrate them into their work routines will determine how quickly AI translates into higher output.
Labor-market flexibility could also affect the scale of productivity gains, with greater worker mobility enabling smoother transitions into roles where AI can be most effective.